Research on the Path of Intelligent Construction of Medical Centers Driven by Artificial Intelligence

The construction of medical centers demands the integration of advanced technologies for accurate cost estimation, resource allocation, and workflow optimization, making these tasks increasingly intricate. Artificial intelligence (AI) plays a revolutionary role by enabling sophisticated path preparation and even prediction. AI-driven methodologies, including machine learning (ML) algorithms and intelligent path planning systems, were explored to optimize construction process and expenditure assessment. 200 medical center construction project datasets were utilized, with preprocessing stages utilizing mean imputation for absent data, min-max scaling to normalize, and dimension decrease by applying principle component analysis (PCA). The usage of AI-based path planning techniques is implemented for resource optimization, reducing construction delay, and site logistics optimization. Furthermore, it developed the Smart Tasmanian Devil-Enhanced Adaptive Gradient Boosting System (STD-AGB) that reached a direct cost assessment accuracy of 97% in the early stage of project initiation. The 12 critical factors affecting cost and construction efficiency included site preparation and electrical works, which demonstrated standard percentage errors of 8.02% and 5.11%, respectively. Such consequences underscore the probable responsibility of AI in refining path planning so that improved outcomes can be achieved and innovation in the intelligent construction of medical centers can be encouraged. A strong framework for integrating AI into healthcare infrastructure development, guarantee optimal workflows and reduced risk, was further established.